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OLIVE YIELDS FORECASTS AND OIL PRICE TRENDS IN MEDITERRANEAN AREAS: A COMPREHENSIVE ANALYSIS OF THE LAST TWO DECADES

Published online by Cambridge University Press:  29 February 2016

F. ORLANDI ,
F. AGUILERA ,
C. GALÁN ,
M. MSALLEM  and
M. FORNACIARI
F. ORLANDI
Affiliation:
Department of Civil and Environmental Engineering, University of Perugia, Borgo XX Giugno 74, 06121, Perugia, Italy
F. AGUILERA*
Affiliation:
Department of Animal Biology, Plant Biology and Ecology, University of Jaen, Agrifood Campus of International Excellence (CeiA3), Campus de Las Lagunillas, 23071, Jaen, Spain
C. GALÁN
Affiliation:
Department of Botany, Ecology and Plant Physiology, University of Cordoba, Agrifood Campus of International Excellence (CeiA3), Campus of Rabanales, 14071, Cordoba, Spain
M. MSALLEM
Affiliation:
Institut de l'Olivier, BP 208, 1082 Tunis, Tunisia
M. FORNACIARI
Affiliation:
Department of Civil and Environmental Engineering, University of Perugia, Borgo XX Giugno 74, 06121, Perugia, Italy
*
‡Corresponding author. Email: faguiler@ujaen.es
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Summary

The main objective of this research was to utilize pollen monitoring methodology to predict olive yields in three Mediterranean olive cultivation areas (Spain, Italy and Tunisia) and their relationships with the olive oil price dynamics. Moreover, olive yield and olive oil production compared with olive oil price trends in the last two decades was evaluated. The statistical analyses confirmed that biological parameters such as the pollen emission, the pollen season start (Pss), the full flowering (Ff) date or the pollen season length (Psl) showed positive correlation values with productive parameters, especially the Pollen Index (Pi). However, the difficulty to define clear relationships with oil price for optimizing the marketing strategies can be due to the olive sector European policy and to the complex international olive oil market situation. The occurrence of unharvested trees was increased and the reduction in agricultural operations as well as non-harvesting could become more widespread above all in traditional extensive systems.

Type
Research Article
Information
Experimental Agriculture , Volume 53 , Issue 1 , January 2017 , pp. 71 - 83
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Copyright
Copyright © Cambridge University Press 2016 

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References

REFERENCES

Aguilera, F. and Ruiz-Valenzuela, L. (2009). Study of the floral phenology of Olea europaea L. in Jaen province (SE Spain) and its relation with pollen emission. Aerobiologia 25:217–225.Google Scholar
Aguilera, F. and Ruiz-Valenzuela, L. (2014). Forecasting olive crop yields based on long-term aerobiological data series and bioclimatic conditions for the southern Iberian Peninsula. Spanish Journal of Agricultural Research 12 (1):215–224.Google Scholar
Aguilera, F. et al. (2015). Phenological models to predict the main flowering phases of olive (Olea europea L.) along a latitudinal and longitudinal gradient across the Mediterranean region. International Journal of Biometeorology 59:629–641.Google Scholar
Barranco, D., Fernández-Escobar, R. and Rallo, L. (eds). (2008). Olive Cultivation, 6th edn., Sevilla, Spain: Junta de Andalucía y Ediciones Mundi-Prensa. p 846. [In Spanish].Google Scholar
Bastiaanssen, W. G. M. and Ali, S. (2003). A new crop yield forecasting model based on satellite measurements applied across the Indus Basin, Pakistan. Agriculture, Ecosystems and Environment 94 (3):321–340.Google Scholar
Bouman, B. A. M., Van Keulen, H., Van Laar, H. H. and Rabbinge, R. (1996). The “School of de Wit” crop growth simulation models: pedigree and historical overview. Agricultural Systems 52:171–198.Google Scholar
Cour, P. (1974). Nouvelles techniques de d´etection des flux et des retombées polliniques: étude de la sedimentation des pollens et des spores à la surface du sol. Pollen et Spores 16:103–141.Google Scholar
European Commission Directorate-General for Agriculture and Rural Development (EC-DGAGRI). (2012). Economic analysis of the olive sector. http://ec.europa.eu/agriculture/oliveoil/economicanalysis_en.pdf. Latest update: July 2012.Google Scholar
Fei, T., Wenbin, W., Dandan, L., Zhongxin, C., Qing, H. and Tian, X. (2012). Yield estimation of winter wheat in North China Plain by using crop growth monitoring system (CGMS). In First International Conference on Agro-Geoinformatics, 2–4 August 2012, Shangai, China, pp. 1–4.Google Scholar
Fornaciari, M., Orlandi, F. and Romano, B. (2005). Yield forecasting for olive trees: A new approach in a historical series (Umbria, Central Italy). Agronomy Journal 97:1537–1542.Google Scholar
Fornaciari, M., Pieroni, L., Orlandi, F. and Romano, B. (2002). A new approach to consider the pollen variable in forecasting yield models. Economic Botany 56:66–72.Google Scholar
Galán, C., García-Mozo, H., Vázquez, L., Ruiz, L., Díaz de la Guardia, C. and Domínguez-Vilches, E. (2008). Modelling olive (Olea europaea L.) crop yield in Andalusia Region, Spain. Agronomy Journal 100 (1):98–104.Google Scholar
Galán, C., Smith, M., Thibaudon, M., Frenguelli, G., Oteros, J., Gehrig, R., Berger, U., Clot, B. and Brandao, R, EAS QC Working Group. (2014). Pollen monitoring: Minimum requirements and reproducibility of analysis. Aerobiologia 30:385–395.Google Scholar
Galán, C., Vázquez, L., García-Mozo, H. and Domínguez-Vilches, E. (2004). Forecasting olive (Olea europaea L.) crop yield based on pollen emission. Field Crop Research 86:43–51.Google Scholar
García-Mozo, H., Domínguez-Vilches, E. and Galán, C. (2012). A model to account for variations in holm-oak (Quercus ilex subsp. ballota) acorn production in southern Spain. Annals of Agricultural and Environmental Medicine 19:411–416.Google Scholar
GEIE Agrosynergie. (2009). Evaluation of measures applied under the common agricultural policy to the olive sector. November 2009 (FR), Framework contract n° 30-CE-0197396/00-06. http://ec.europa.eu/agriculture/eval/reports/oilseeds/exec_sum_en.pdf).Google Scholar
Hirst, J. M. (1952). An automatic volumetric spore trap. Annals of Applied Biology 39:257–265.Google Scholar
Loumou, A. and Giourga, C. (2003). Olive groves: The life and identity of the Mediterranean. Agriculture Human Values 20:87–95.CrossRefGoogle Scholar
Orlandi, F., Bonofiglio, T., Romano, B. and Fornaciari, M. (2012). Qualitative and quantitative aspects of olive production in relation to climate in southern Italy. Scientia Horticulturae 138:151–158.CrossRefGoogle Scholar
Orlandi, F., García-Mozo, H., Ben Dhiab, A., Galán, C., Msallem, M. and Fornaciari, M. (2014a). Olive tree phenology and climate variations in the Mediterranean area over the last two decades. Theoretical and Applied Climatology 115:207–218.Google Scholar
Orlandi, F., García-Mozo, H., Ben Dhiab, A., Galán, C., Msallem, M., Romano, B., Abichou, M., Domínguez-Vilches, E. and Fornaciari, M. (2013). Climatic indices in the interpretation of the phenological phases of the olive in Mediterranean areas during its biological cycle. Climatic Change 116:263–284.Google Scholar
Orlandi, F., Oteros, J., Aguilera, F., Ben Dhiab, A., Msallem, M. and Fornaciari, M. (2014b). Design of a downscaling method to estimate continuous data from discrete pollen monitoring in Tunisia. Environmental Sciences: Processes Impacts 16:1716–1725.Google Scholar
Orlandi, F., Romano, B. and Fornaciari, M. (2005). Effective pollination period estimation in olive (Olea europaea L.): A pollen monitoring application. Scientia Horticulturae 105:313–318.Google Scholar
Orlandi, F., Sgromo, C., Bonofiglio, T., Ruga, L., Romano, B. and Fornaciari, M. (2010). Yield modelling in a Mediterranean species utilizing cause-effect relationships between temperature forcing and biological processes. Scientia Horticulturae 123:412–417.Google Scholar
Oteros, J., García-Mozo, H., Hervás, C. and Galán, C. (2013a). Biometeorological and autoregressive indices for predicting olive pollen intensity. International Journal of Biometeorology 57 (2):307–316.Google Scholar
Oteros, J., García-Mozo, H., Hervás, C. and Galán, C. (2013b). Year clustering analysis for modelling olive flowering phenology. International Journal of Biometeorology 57 (4):545–555.Google Scholar
Oteros, J. et al. (2014). Better prediction of Mediterranean olive production using pollen-based models. Agronomy for Sustainable Development 34:685–694.Google Scholar
Palm, R. (1995). Regression methods including the Eurostat Agromet model and time trends. Joint Research Centre of the E.U. Publication EUR 16008 EN, of the Office for Official Publications of the E.U. Luxembourg, pp. 61–72.Google Scholar
Ribeiro, H., Cunha, M. and Abreu, I. (2008). Quantitative forecasting of olive yield in northern Portugal using a bioclimatic model. Aerobiologia 24:141–150.Google Scholar
Saavedra, M. M. and Pastor, M. (2002). Sistemas de cultivo en olivar. Manejo de malas hierbas y herbicidas. S.A., Madrid, Spain: Editorial Agrícola Española. p. 439. [In Spanish].Google Scholar
Salmi, T., Määttä, A., Anttila, P., Ruoho-Airola, T. and Amnell, T. (2002). Detecting trends of annual values of atmospheric pollutants by the Mann-Kendall test and Sen's slope estimates—the Excel template application Makesens. Publications on Air Quality No. 31. Finnish Meteorological Institute. Helsinki, Finland.Google Scholar
Sánchez-Martínez, J. D., Gallego-Simón, V. J. and Jiménez, E. A. (2008). El monocultivo olivarero jiennense: ¿del productivismo a la sostenibilidad?. Boletín de la A.G.E. 47:245–270.Google Scholar
Sirois, A. (1998). A brief and biased overview of time series or how to find that evasive trend. In WMO report No. 133: WMO/EMEP workshop on Advanced Statistical methods and their application to Air Quality Data sets, Helsinki, 14–18 September 1998.Google Scholar
Siskosa, Y., Matsatsinisa, N. F. and Baourakis, G. (2001). Multicriteria analysis in agricultural marketing: The case of French olive oil market. European Journal of Operational Research 130 (2):315–331.Google Scholar